(self, quantized_residual, seg_idx, salience_level=None)
| 112 | return residual_quantized, salience_level, key_point_map |
| 113 | |
| 114 | def dequantize_residual(self, quantized_residual, seg_idx, salience_level=None): |
| 115 | residual = np.zeros_like(seg_idx, dtype=np.float32) |
| 116 | start = 0 |
| 117 | for m in range(seg_idx.max() + 1): |
| 118 | idx = np.where(seg_idx == m) |
| 119 | if m == 1: |
| 120 | # zero points |
| 121 | continue |
| 122 | |
| 123 | if self.uniform: |
| 124 | cur_acc = self.acc |
| 125 | else: |
| 126 | cur_acc = self.acc[salience_level[m]] |
| 127 | residual[idx] = quantized_residual[start:start + idx[0].shape[0]] * cur_acc |
| 128 | start += idx[0].shape[0] |
| 129 | if start != quantized_residual.shape[0]: |
| 130 | print('not correct.') |
| 131 | IPython.embed() |
| 132 | return np.expand_dims(residual, -1) |
| 133 | |
| 134 | |
| 135 | # numpy to bytes |
no outgoing calls
no test coverage detected